Quantitative data analysis makes sense of numerical data. We can use numbers
to summarise the experiences or characteristics of a group of participants,
for example their average age or the number of symptoms they report. We can
also use numbers to look at people’s behaviours, experiences and views.
Perhaps most importantly, we can use numbers to look at differences between
groups of people or the same group over time. This can help us understand
the effect of new treatment or policy initiatives, both in terms of the type
of effect (e.g. does a new policy make things better, worse or leave things
unchanged?) and the size of its impact (e.g. are any changes big enough to
be meaningful or could they have happened just by chance?). This chapter
explores some of the different approaches to analysing numerical data,
examines the difference between descriptive and inferential statistics, and
highlights some of the ways in which you can begin to interpret research
data presented as numbers.

Related Content

Related Content

Chapter

Publication History:

Quantitative research uses large samples and, as such, the findings of
well-conducted studies can often be generalised to larger populations.
However, it is important that studies are well-designed to avoid errors in
their interpretation and/or the reporting of inaccurate results. Misleading
results from quantitative studies can have serious negative implications
such as wasting public money on flawed policies and subjecting service users
to ineffective or harmful treatments. This chapter explores descriptive and
experimental quantitative research designs and examines, through case
examples, the difference between cross-sectional, longitudinal and cohort
studies. Factors leading to poorly and well-constructed studies are
explored, along with a discussion of the key features of well-designed
randomised controlled trials, the gold-standard design for testing treatment
effectiveness.

Chapter

Publication History:

This chapter defines and introduces the different stages of the research
process: from identifying a problem, to reviewing the literature; then
developing a research question; designing a study; obtaining funding and
ethical approval; recruiting participants; collecting and analysing data;
and reporting and disseminating findings. This chapter outlines how users of
health services, their carers and family members, and other members of the
public can be involved in these different research stages, and demonstrates
the impact that this involvement can have. Examples of different ways of
involving and engaging public members in research studies are drawn from the
Enhancing the Quality of User-Involved Care Planning in Mental Health
Services (EQUIP) research programme.